Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 899 481 749 140 396 732 662 750 550 382 665 243 851 309 597 288 978 354 862 563
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 354 851 750 140 396 NA 309 749 978 243 862 NA 732 NA 899 563 665 662 550 382 597 288 481
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 1 2 5 2 2 1 1 2 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y"
[26] "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y"
[26] "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "j" "m" "l" "h" "o" "B" "U" "M" "H" "N"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 17
which( manyNumbersWithNA > 900 )
[1] 9
which( is.na( manyNumbersWithNA ) )
[1] 6 12 14
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 978
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 978
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 978
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "B" "U" "M" "H" "N"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "j" "m" "l" "h" "o"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE
[18] TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 2 5 9 10 14 15 18 20
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" "large" "small" "small" NA "small" "large" "large" "small" "large" NA
[13] "large" NA "large" "large" "large" "large" "large" "small" "large" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "large" "small" "small" "UNKNOWN" "small" "large" "large" "small"
[11] "large" "UNKNOWN" "large" "UNKNOWN" "large" "large" "large" "large" "large" "small"
[21] "large" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 851 750 0 0 NA 0 749 978 0 862 NA 732 NA 899 563 665 662 550 0 597 0 0
unique( duplicatedNumbers )
[1] 3 1 2 5
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 1 2 5
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 9
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 978
which.min( manyNumbersWithNA )
[1] 4
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 140
range( manyNumbersWithNA, na.rm = TRUE )
[1] 140 978
manyNumbersWithNA
[1] 354 851 750 140 396 NA 309 749 978 243 862 NA 732 NA 899 563 665 662 550 382 597 288 481
sort( manyNumbersWithNA )
[1] 140 243 288 309 354 382 396 481 550 563 597 662 665 732 749 750 851 862 899 978
sort( manyNumbersWithNA, na.last = TRUE )
[1] 140 243 288 309 354 382 396 481 550 563 597 662 665 732 749 750 851 862 899 978 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 978 899 862 851 750 749 732 665 662 597 563 550 481 396 382 354 309 288 243 140 NA NA NA
manyNumbersWithNA[1:5]
[1] 354 851 750 140 396
order( manyNumbersWithNA[1:5] )
[1] 4 1 5 3 2
rank( manyNumbersWithNA[1:5] )
[1] 2 5 4 1 3
sort( mixedLetters )
[1] "B" "h" "H" "j" "l" "m" "M" "N" "o" "U"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 8.0 2.5 8.0 8.0 8.0 5.0 2.5 8.0 4.0 1.0
rank( manyDuplicates, ties.method = "min" )
[1] 6 2 6 6 6 5 2 6 4 1
rank( manyDuplicates, ties.method = "random" )
[1] 9 3 7 6 10 5 2 8 4 1
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.2424731 1.2091964 -1.1128111 2.6169423
[10] 0.6615275 1.4556635 -0.9116678 0.8900952 -0.4266855 0.5394654
round( v, 0 )
[1] -1 0 0 0 1 0 1 -1 3 1 1 -1 1 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.2 1.2 -1.1 2.6 0.7 1.5 -0.9 0.9 -0.4 0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.24 1.21 -1.11 2.62 0.66 1.46 -0.91 0.89 -0.43 0.54
floor( v )
[1] -1 -1 0 0 1 0 1 -2 2 0 1 -1 0 -1 0
ceiling( v )
[1] -1 0 0 1 1 1 2 -1 3 1 2 0 1 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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